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Background: Dysphagia, a common complication after stroke, significantly hampers the recovery process of patients, both due to dysphagia itself and the additional complications it causes. Although a large number of articles have been published on post‐stroke dysphagia (PSD), bibliometric analysis in this field is still lacking. This study aimed to provide a comprehensive understanding of the research hotspots and trends in PSD, thereby guiding future research efforts. Methods: The Web of Science Core Collection (WoSCC) database was searched for articles related to PSD from 2003 to 2022. Data were visualised and analysed using CiteSpace and VOSviewer. Results: A total of 3102 publications were included in the scientometric analysis, with a gradual increase in the number of papers published each year. The United States emerged as the country with the highest number of publications (625 articles), while the University of Manchester led with the most publications among institutions (67 articles). Notably, Dysphagia was both the most published (254 articles) and the most cited journal (11,141 citations). Among authors, Hamdy S emerged as the most prolific (52 articles), with Martino R being the most cited (1042 citations). Conclusion: Based on our findings, we anticipate that research hotspots in PSD will mainly focus on complications due to PSD such as stroke‐associated pneumonia, stroke‐related sarcopenia. Additionally, exploration into the mechanisms and parameters of noninvasive brain stimulation techniques for the treatment of PSD, as well as the rehabilitation needs of patients with PSD, are expected to be key focal points in future research endeavours. [ABSTRACT FROM AUTHOR]

Rationale, aims and objectives: The Patient Assessment of Chronic Illness Care (PACIC) instrument assesses patient care in alignment with the chronic care model. The aim of the study was to comprehensively validate the PACIC using the Rasch model. A special focus was placed on the investigation of local dependence (LD), differential item functioning (DIF) and targeting. Method: This secondary analysis utilized data of 760 patients with a diagnosis of diabetes who had participated in the Swiss CoDiab‐VD cohort study. The psychometric properties of the French PACIC‐version were evaluated using the Rasch model. DIF was investigated in relation to age, gender, education, year of recruitment into the CoDiab‐VD cohort study, type of diabetes and whether patients got an injectable antidiabetic drug or not. Results: The initial analysis of the PACIC revealed poor fit to the Rasch model (χ2‐p < 0.001) with response dependency being the most prominent problem. After combining the items into two testlets (testlet 1: Items 1–11; testlet 2: Items 12–20), good overall model fit was found (χ2‐p = 0.77) as well as good reliability (Person Separation Index = 0.85) and targeting. DIF with regard to whether patients got an injectable antidiabetic drug or not was found for testlet 2. However, the size of this DIF was regarded as not being substantial. Conclusion: The PACIC is a well‐targeted, reliable unidimensional instrument to assess patient care in alignment with the chronic care model in patients with diabetes. It is free of substantial DIF. The PACIC‐20 sum score can hence be used in clinical practice for individual diagnostic. For evaluation purposes like assessment of change or group evaluations, the usage of the interval‐scale level person parameters is recommended as it permits using parametric statistical analyses and provides a more accurate picture about the actual amount of change. [ABSTRACT FROM AUTHOR]